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Name: hustee
Type: User
Name: hustee
Type: User
An interesting way of solving the thermal scheduling problem in power systems.
【国赛】【美赛】数学建模相关算法 MATLAB实现
Power Systems Research
Electronic companion for research paper "Data-driven Distributed Operation of Electricity and Natural Gas Systems"
多区域互联电力系统的分布式优化调度方法
for ab102
Electronic companion for research paper "Energy and Reserves Dispatch with Distributionally Robust Joint Chance Constraints"
互联网上的免费书籍
Here I have implemented an optimal power flow with an aim of minimizing active power loss in a power system using genetic algorithm in MATLAB.
MatLab Optimzation Code : The Idea of this Algorithm first we generate random solutions then we start the first part of iteration GA and compare GA results with PSO results and choose best these solution go to PSO Algorithm and create new solution and compare the new solutios with GA and choose best and so on like Cuckoo algorithm ( CA )
The optimal dispatch of CAES in the integrated energy systems
Statistical learning methods, 统计学习方法 [李航] 值得反复读. [笔记, 代码, notebook, 参考文献, Errata, lihang]
Recently, riding through grid faults and supporting the grid voltage by using grid-connected converters (GCCs) have become major requirements reflected in the grid codes. This paper presents a novel reference current generation scheme with the ability to support the grid voltage by injecting a proper set of positive/negative active/reactive currents by using four controlling parameters. Analytical expressions are proposed to obtain the optimal values of these parameters under any grid voltage condition. The optimal performances can be obtained by achieving the following objectives: first, compliance with the phase voltage limits, second, maximized active and reactive power delivery, third, minimized fault currents, and fourth reduced oscillations on the active and reactive powers. These optimal behaviors bring significant advantages to emerging GCCs, such as increasing the efficiency, lowering the dc-link ripples, improving ac system stability, and avoiding equipment tripping. Simulation and experimental results verify the analytical results and the proposed expressions.
Benchmarks for the Optimal Power Flow Problem
Security-Constrained Unit Commitment Programming Project
Implementation of Optimization Techniques for Economic Dispatch of Power Systems
The code is based on Python 3 and gurobi
Code for IEEE Transactions: A Two-Layer Energy Management System for Microgrids With Hybrid Energy Storage Considering Degradation Costs.
The windML framework provides an easy-to-use access to wind data sources within the Python world, building upon numpy, scipy, sklearn, and matplotlib. Renewable Wind Energy, Forecasting, Prediction
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.